摘要
本文提出了一种基于微粒群(PSO)算法优化的微硅加速度传感器动态误差补偿器的设计方法。该方法无需事先已知微硅加速度传感器的动态特性,可根据传感器以及参考模型对输入激励响应的实测数据,通过PSO算法的优化学习得到补偿器的参数。传感器的输出经过补偿器后,能够克服由动态特性引起的测量误差。最后,通过实验验证了该方法的有效性。
A design method to optimize the dynamic errors of the compensator for micro-silicon accelerometer is presented, which is based on particle swarm optimization （PSO）. With this method a dynamic compensator can be realized without knowing the dynamic characteristics of the sensor, the parameter of the compensator is optimized using PSO algorithm according to the measurement data of the step response of the sensor and the reference model. After the sensor output signal is processed by the compensator, the dynamic measurement errors are reduced. Experimental results show that the method is effective.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2006年第12期1707-1710,共4页
Chinese Journal of Scientific Instrument
基金
国家自然科学基金(60474079)
江苏省高校自然科学基金(06KJD520099)资助项目
关键词
微硅加速度器
动态误差
补偿
参数优化
微粒群算法
micro-silicon accelerometer dynamic error compensation parameter optimization particle swarm optimization
